401: BIOINFORMATICS
(Optional 1)
Unit I
1. Over view of Bioinformatics: Merger of life sciences with computers.
2. Search engines: Google, Pub Med, NCBI, EMBL,
3. Protein and DNA databases: Swiss port, PIR, OMIM, Embank, ENTREZ, DDJB,
MIPS, Hovered, ECDC, Cambridge small molecular crystal structure data bank.
4. Analysis packages: Commercial databases and packages, GPL software for
bioinformatics, web based analysis protocol.
Unit II
1 Sequence Databases: Contents, Structure, and annotation for Human Genome
Databases, Plant Genome Databases, Retrieving and installing a programme (Tree
Tool), Multiple sequence alignment programme - Clustal W , X.
2. Genome analysis programs; BLAST, FASTA, CGC, Motif and profile
Sequence search.
3. Phylogenetic analysis: Phylogenetic reconstruction, distance matrices, Parsimony,
Philip.
4. Data models: Instances and schemes; E-R Model, E-R diagrams, reducing E-R diagrams
to tables, network data model.
Unit III
1. Methods of prediction of Proteins, DNA, RNA, fold recognition , Ab initio methods for
structure prediction
2. Computer aided drug designing: Basic principles, docking, ADME/TOX
3. Genome mapping applications: EST and Functional genomics, EST clustering gene
discovery, ORF prediction.
4. Use of genome analysis programs, primer designing tools.
Unit IV
1. Cluster analysis; Phylogenetic clustering by simple matching coefficients
2. Sequence Comparison; Sequence pattern; Regular expression based pattern; Theory of
profiles and their use in sequence analysis
3. Markov models; Concept of HMMS; Baum-Welch algorithm; Use of profile HMM for
protein family classification; Pattern recognition methods
4. Structure determination: X-ray crystallography; NMR spectroscopy; PDB (protein data
bank) and NDB (nucleic acid data bank); File formats for the storage and dissemination
of molecular structure
Unit V
1. Modeling and conformational analysis: Homology modeling; Threading and protein
structure prediction
2. Force fields; Molecular energy minimization
Monte Carlo and molecular dynamics simulation
3. Tagging of genes and molecular modeling
4. Modeling & Drug design
Practical Exercises: Appropriate exercises based on public data bases
References
1. Introduction to Bioinformatics: Theoretical and practical approach by Stephen A
Krawetz and DD Womble.
2. Bioinformatics genes, proteins and computers by CA Orengo, DT Jopnes and JM
Thornton
3. An Introduction to computational Biochemistry by C Stan T Sai
4. Instant Notes on Bioinformatics By DR Westhead, JM Perish and RM Toyman
5. Essential Bioinformatics by Jin Xiong
6. An Introduction to Bioinformatics Algorithms by by Neil C. Jones, Pavel Pevzner
7. Bioinformatics: Sequence and Genome Analysis by by David W. Mount
8. Statistical Methods in Bioinformatics: An Introduction by Stephen Misener, Stephen A.
Krawetz
9. Bioinformatics: databases and algorithms by N. Gautham
10. Bioinformatics Technologies by Yi-Ping Phoebe Chen
11. Data Mining: Multimedia, Soft Computing, and Bioinformatics
by Sushmita Mitra, Tinku Acharya
